@inproceedings{fc4b8774a1924b778a0f93c2ee2626a4,
title = "Improving video-based iris recognition via local quality weighted super resolution",
abstract = "In this paper we address the problem of iris recognition at a distance and on the move. We introduce two novel quality measures, one computed Globally (GQ) and the other Locally (LQ), for fusing at the pixel level the frames (after a bilinear interpolation step) extracted from the video of a given person. These measures derive from a local GMM probabilistic characterization of good quality iris texture. Experiments performed on the MBGC portal database show a superiority of our approach compared to score-based or average image-based fusion methods. Moreover, we show that the LQ-based fusion outperforms the GQ-based fusion with a relative improvement of 4.79\% at the Equal Error Rate functioning point.",
keywords = "Fusion of images, Iris recognition, Quality, Super resolution, Video",
author = "Nadia Othman and Nesma Houmani and Bernadette Dorizzi",
year = "2013",
month = may,
day = "27",
language = "English",
isbn = "9789898565419",
series = "ICPRAM 2013 - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods",
pages = "623--629",
booktitle = "ICPRAM 2013 - Proceedings of the 2nd International Conference on Pattern Recognition Applications and Methods",
note = "2nd International Conference on Pattern Recognition Applications and Methods, ICPRAM 2013 ; Conference date: 15-02-2013 Through 18-02-2013",
}